videodb

Ingest and index multimedia from files, URLs, RTSP streams, and desktop captures.

1|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/devs6186/claude-private-skills-agents-commands --skill videodb-devs6186
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: videodb
Source: https://github.com/devs6186/claude-private-skills-agents-commands/tree/main/skills/videodb
Command: npx skills add https://github.com/devs6186/claude-private-skills-agents-commands --skill videodb-devs6186

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires videodb, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Video teams struggle to manually index, search, and edit large libraries of footage across formats and live streams. This skill automates ingestion, indexing, and production workflows for video and audio content, enabling fast retrieval and playback. It coordinates server-side processing to extract frames, build visual/semantic/temporal indexes, and enable precise search with timestamps and auto-clips, while supporting real-time alerts from live streams or desktop capture.

Core Features & Use Cases

  • Ingest media from local files, URLs, RTSP/live feeds, or live desktop captures.
  • Build visual, semantic, and temporal indexes for fast search, clips, and evidence links.
  • Transcode, normalize, and generate playable streams and alerts for live or recorded content.
  • Create timeline edits (subtitles, overlays, branding, audio overlays, dubbing, translation) and generate media assets (image, audio, video).
  • Use Case: Build a searchable video library from a conference recording and publish highlight streams.

Quick Start

Ingest a local video file, index spoken words and visuals, then generate a playable stream.

Frequently Asked Questions about videodb

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I index and search across multiple live RTSP streams and local video files?

Server-side video indexing handles RTSP streams and local files by extracting frames and building visual, semantic, and temporal indexes. This enables fast retrieval and searchable playback across both live and recorded content without local encoding.

What is AI-powered video indexing and how does it enable timestamped search?

AI-powered video indexing is the process of extracting frames and building semantic indexes from multimedia content. It enables precise timestamped search by analyzing spoken words and visuals, allowing you to retrieve exact moments across recorded footage and live streams.

How do I build a searchable video library from conference recordings?

Build a searchable video library from conference recordings by ingesting media files to build semantic and temporal indexes. You can then search for spoken words or visuals, generate playable highlight streams, and create timeline edits with subtitles and overlays.

Does server-side video processing support real-time alerts from desktop capture?

Server-side video processing supports real-time alerts from desktop capture by ingesting and indexing live captures. The system monitors visual and semantic data to automatically generate alerts without requiring local encoding on your machine.

Can I add subtitles, overlays, and dubbing to video clips generated from search results?

You can add subtitles, overlays, branding, audio overlays, dubbing, and translation to video clips generated from search results. The platform handles timeline editing and transcoding to produce final playable streams and media assets from indexed footage.

What are the limitations of relying on server-side processing for video transcoding and indexing?

Relying on server-side processing for video transcoding and indexing requires continuous server connectivity for frame extraction and stream generation. Heavy ingestion workloads may also introduce processing latency for large video libraries and live RTSP feeds.